Systems and methods for motion signal correction

ABSTRACT

The present disclosure describes systems and methods for determining whether a motion signal derived from image data relating to a subject is synchronous with the actual motion state of the subject. The method may include determining one or more values of a symmetry related parameter of a motion signal. The method may further include correcting the motion signal if the motion signal is determined flipped.

TECHNICAL FIELD

The application generally relates to systems and methods for signalprocessing, and more specifically relates to systems and methods forcorrecting a motion signal.

BACKGROUND

Respiratory gating may reduce the effects of respiratory motion in imagereconstruction, such as Emission Computed Tomography (ECT) imagereconstruction. A respiratory motion signal may be needed for therespiratory gating. In some embodiments, a data-driven technique may beused to extract a respiratory motion signal. Limited by factorsincluding, for example, the algorithm itself applied in a data-driventechnique, the field of view of the image scanner used to acquire imagedata to be analyzed, the data-driven technique may extract respiratorymotion signals that have flipped phases. The direct use of suchrespiratory motion signals may be troublesome for the determination ofinspiration/expiration phases of the respiratory motion. Furthermore,the uncertainty on the inspiration/expiration phases of the respiratorymotion may cause inaccurate motion correction of an image.

SUMMARY

Additional features will be set forth in part in the description whichfollows, and in part will become apparent to those skilled in the artupon examination of the following and the accompanying drawings or maybe learned by production or operation of the examples. The features ofthe present disclosure may be realized and attained by practice or useof various aspects of the methodologies, instrumentalities andcombinations set forth in the detailed examples discussed below.

According to an aspect of the present disclosure, a method forcorrecting a motion signal is provided. The method may be implemented onat least one machine each of which has at least one processor andstorage. The method may include acquiring a motion signal. The methodmay further include determining one or more values of a symmetry relatedparameter of the motion signal. The method may further includedetermining that the motion signal is flipped based on the one or morevalues of the symmetry related parameter. The method may further includecorrecting, in response to the determination that the motion signal isflipped, the motion signal.

In some embodiments, the acquiring a motion signal may include acquiringa respiratory motion signal based on Emission Computed Tomography (ECT)data.

In some embodiments, the determining one or more values of a symmetryrelated parameter of the motion signal may include determining areference line with respect to the motion signal.

In some embodiments, the motion signal may include a respiratory motionsignal, the determining one or more values of a symmetry relatedparameter of the motion signal may include identifying an end of acandidate inspiration phase (candidate EIP) and an end of a candidateexpiration phase (candidate EEP) in the respiratory motion signal basedon the reference line, wherein an amplitude of the candidate EIP is apeak amplitude of the respiratory motion signal, and an amplitude of thecandidate EEP is a valley amplitude of the respiratory motion signal,wherein the reference line is midway between the candidate EIP and thecandidate EEP such that the amplitude of the candidate EIP is equal tothe amplitude of the candidate EEP; and determining the one or morevalues of the symmetry related parameter of the motion signal based on aduration related to the candidate EIP and a duration related to thecandidate EEP.

In some embodiments, the motion signal may include a respiratory motionsignal, the determining one or more values of a symmetry relatedparameter of the motion signal may include determining a durationrelated to a candidate inspiration phase and a duration of a candidateexpiration phase based on the reference line, wherein the reference lineis such that the duration of the candidate inspiration phase is equal tothe duration of the candidate expiration phase; identifying one or moreends related to the candidate inspiration phases (candidate EIPs) andone or more ends of the candidate expiration phase (candidate EEPs);determining a peak amplitude of the one or more candidate EIPs of themotion signal with respect to the reference line, and a valley amplitudeof the one or more candidate EEPs of the motion signal with respect tothe reference line; and determining the one or more values of thesymmetry related parameter of the motion signal based on the peakamplitude and the valley amplitude.

In some embodiments, the motion signal comprising a respiratory motionsignal, the determining a reference line of the motion signal mayinclude determining a reference line of the respiratory motion signalbased on a first criterion including a combination of an amplitude and aduration of the respiratory motion signal.

In some embodiments, the determining one or more values of a symmetryrelated parameter of the motion signal may include determining one ormore values of the symmetry related parameter of the respiratory motionsignal based on a second criterion including a combination of a weightedamplitude and the duration of the respiratory motion signal with respectto the reference line.

In some embodiments, the determining that the motion signal is flippedmay include determining credibility of the one or more values of thesymmetry related parameter.

In some embodiments, the determining credibility of the one or morevalues of the symmetry related parameter may include determining whetherthe one or more values of the symmetry related parameter are below afirst threshold; or determining whether a duration of the respiratorymotion signal is less than a second threshold; or determining avariation among the one or more values of the symmetry relatedparameter; or determining whether a signal to noise ratio correspondingto the respiratory motion signal exceeds a third threshold.

In some embodiments, the determining that the motion signal is flippedmay include determining, in response to a determination that the one ormore values of the symmetry related parameter are incredible, that therespiratory motion signal is flipped based on a plurality of imagesreconstructed based on the ECT data.

In some embodiments, each frame of the plurality of frames of the ECTdata may correspond to a same number of ECT events.

In some embodiments, the determining that the respiratory motion signalis flipped based on a plurality of images reconstructed based on the ECTdata may include gating, based on the respiratory motion signal, the ECTdata into a plurality of frames; reconstructing the plurality of images,an image of the plurality of images corresponding to a frame of theplurality of frames of the ECT data; registering at least two of theplurality of images; determining a motion of a point of interest basedon the registration; and determining that the respiratory motion signalis flipped based on the motion of the point of interest.

In some embodiments, each frame of the plurality of frames of the ECTdata may correspond to a same amplitude interval, or a same timeinterval.

In some embodiments, the registering at least two of the plurality ofimages may include registering the at least two of the plurality ofimages based on an approach of sum square error (SSE).

According to an aspect of the present disclosure, a method forcorrecting a motion signal is provided. The system may include anacquisition module that is configured to obtain ECT data relating to asubject. The system may further include a processing module. Theprocessing module may include a respiratory motion signal acquisitionunit that is configured to acquire a respiratory motion signal based onthe ECT data. The processing module may further include a symmetrydetermination unit that is configured to determine one or more values ofa symmetry related parameter of the respiratory motion signal. Theprocessing module may further include a flip determination unit that isconfigured to determine that the respiratory motion signal is flippedbased on the one or more values of the symmetry related parameter. Theprocessing module may further include a correction unit that isconfigured to correct, in response to the determination that therespiratory motion signal is flipped, the respiratory motion signal.

According to an aspect of the present disclosure, a method forcorrecting a motion signal is provided. The method may be implemented onat least one machine, each of which has at least one processor andstorage. The method may include acquiring ECT data of a subject, anddetermining a motion signal based on the ECT data. The method mayfurther include determining that the motion signal is flipped. Themethod may further include correcting the motion signal if thedetermination that the motion signal is flipped.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is further described in terms of exemplaryembodiments. These exemplary embodiments are described in detail withreference to the drawings. These embodiments are non-limiting exemplaryembodiments, in which like reference numerals represent similarstructures throughout the several views of the drawings, and wherein:

FIG. 1-A is a schematic diagram illustrating an exemplary imaging systemaccording to some embodiments of the present disclosure;

FIG. 1-B is a block diagram illustrating an exemplary processing engineaccording to some embodiments of the present disclosure;

FIG. 1-C is a schematic diagram illustrating an exemplary computingdevice according to some embodiments of the present disclosure;

FIG. 1-D is a schematic diagram illustrating exemplary hardware and/orsoftware components of an exemplary mobile device according to someembodiments of the present disclosure;

FIG. 2 is a block diagram illustrating an exemplary processing moduleaccording to some embodiments of the present disclosure;

FIG. 3 is a flowchart illustrating an exemplary process for correcting amotion signal according to some embodiments of the present disclosure;

FIG. 4 is a flowchart illustrating an exemplary process for determiningone or more values of a symmetry related parameter of a motion signalaccording to some embodiments of the present disclosure;

FIG. 5 is a block diagram illustrating an exemplary flip determinationunit according to some embodiments of the present disclosure;

FIG. 6 is a flowchart illustrating an exemplary process for determiningwhether a respiratory motion signal is flipped according to someembodiments of the present disclosure;

FIG. 7 is a flowchart illustrating an exemplary process of determiningwhether a motion signal is flipped according to some embodiments of thepresent disclosure;

FIG. 8 is a flowchart illustrating an exemplary process for gating theECT data according to some embodiments of the present disclosure;

FIG. 9 is a block diagram illustrating an exemplary credibilitydetermination sub-unit according to some embodiments of the presentdisclosure;

FIG. 10 is a flowchart illustrating an exemplary process for determiningcredibility of one or more values of a symmetry related parameteraccording to some embodiments of the present disclosure;

FIG. 11 illustrates an exemplary respiratory motion signal according tosome embodiments of the present disclosure;

FIG. 12 illustrates a first exemplary division of a respiratory motionsignal according to some embodiments of the present disclosure;

FIG. 13 illustrates a second exemplary division of a respiratory motionsignal according to some embodiments of the present disclosure; and

FIG. 14 illustrates a third exemplary division of a respiratory motionsignal according to some embodiments of the present disclosure.

DETAILED DESCRIPTION

In the following detailed description, numerous specific details are setforth by way of examples in order to provide a thorough understanding ofthe relevant disclosure. However, it should be apparent to those skilledin the art that the present disclosure may be practiced without suchdetails. In other instances, well known methods, procedures, systems,components, and/or circuitry have been described at a relativelyhigh-level, without detail, in order to avoid unnecessarily obscuringaspects of the present disclosure. Various modifications to thedisclosed embodiments will be readily apparent to those skilled in theart, and the general principles defined herein may be applied to otherembodiments and applications without departing from the spirit and scopeof the present disclosure. Thus, the present disclosure is not limitedto the embodiments shown, but to be accorded the widest scope consistentwith the claims.

The terminology used herein is for the purpose of describing particularexample embodiments only and is not intended to be limiting. As usedherein, the singular forms “a,” “an,” and “the” may be intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprise,”“comprises,” and/or “comprising,” “include,” “includes,” and/or“including,” when used in this specification, specify the presence ofstated features, integers, steps, operations, elements, and/orcomponents, but do not preclude the presence or addition of one or moreother features, integers, steps, operations, elements, components,and/or groups thereof.

It will be understood that the term “system,” “unit,” “module,” and/or“block” used herein are one method to distinguish different components,elements, parts, section or assembly of different level in ascendingorder. However, the terms may be displaced by other expression if theyachieve the same purpose.

It will be understood that when a unit, engine, module or block isreferred to as being “on,” “connected to,” or “coupled to,” anotherunit, engine, module, or block, it may be directly on, connected orcoupled to, or communicate with the other unit, engine, module, orblock, or an intervening unit, engine, module, or block may be present,unless the context clearly indicates otherwise. As used herein, the term“and/or” includes any and all combinations of one or more of theassociated listed items.

These and other features, and characteristics of the present disclosure,as well as the methods of operation and functions of the relatedelements of structure and the combination of parts and economies ofmanufacture, may become more apparent upon consideration of thefollowing description with reference to the accompanying drawings, allof which form a part of this disclosure. It is to be expresslyunderstood, however, that the drawings are for the purpose ofillustration and description only and are not intended to limit thescope of the present disclosure. It is understood that the drawings arenot to scale.

The present disclosure describes systems and methods for determiningwhether a motion signal derived from image data relating to a subject issynchronous with the actual motion state of the subject. For example, adetermination may be made as to whether the motion signal derived fromthe image data is flipped based on one or more values of a symmetryrelated parameter of the motion signal. Furthermore, in response to thedetermination that the motion signal is flipped, the motion signal maybe corrected.

FIG. 1-A is a schematic diagram illustrating an exemplary imaging system100 according to some embodiments of the present disclosure. The imagingsystem 100 may include an emission computed tomography (ECT) system,such as, for example, a positron emission tomography (PET) system, asingle photon emission computed tomography (SPECT) system, amulti-modality system, etc. The imaging system 100 may include amulti-modality system including, for example, a computedtomography-positron emission tomography (CT-PET) system, a magneticresonance-positron emission tomography (MR-PET) system, etc. In someembodiments, the multi-modality system may include modules and/orcomponents for performing ECT imaging and/or related analysis. Merely byway of example, the imaging system 100 may include an ECT scanner 110, anetwork 120, one or more terminals 130, a processing engine 140, and astorage 150.

In some embodiments, the ECT scanner 110, the processing engine 140, thestorage 150, and/or the terminal(s) 130 may be connected to and/orcommunicate with each other via a wireless connection (e.g., the network120), a wired connection, or a combination thereof. The connectionbetween the components in the imaging system 100 may be variable. Merelyby way of example, the ECT scanner 110 may be connected to theprocessing engine 140 through the network 120, as illustrated in FIG. 1.As another example, the ECT scanner 110 may be connected to theprocessing engine 140 directly. As a further example, the storage 150may be connected to the processing engine 140 through the network 120,as illustrated in FIG. 1, or connected to the processing engine 140directly. As still a further example, a terminal 130 may be connected tothe processing engine 140 through the network 120, as illustrated inFIG. 1, or connected to the processing engine 140 directly.

The ECT scanner 110 may include a gantry 111, a detector 112 mounted onthe gantry 111, a detection region 113, and a subject table 114.

The detector 112 may detect radiation events (e.g., gamma photons)emitted from the detection region 113. At least a portion of theradiation events may originate from a subject placed in the detectionregion 113. In some embodiments, the detector 112 may include aplurality of detector units. The detector units may be implemented inany suitable manner, for example, in a ring, in a rectangle, or in anarray. In some embodiments, the detector units may include one or morecrystal elements and/or one or more photomultiplier tubes (PMT). A PMTas employed in the present disclosure may be a single-channel PMT or amulti-channel PMT. The subject table 114 may transfer a patient into thedetection region 113.

In some embodiments, the detected radiation events may be stored orarchived in a storage (e.g., the storage 150 or a storage module in theprocessing engine 140), processed by the processing engine 140, ortransferred to an external processing and/or storage device (e.g., acloud server) via a cable, or a wired or wireless network.

The network 120 may include any suitable network that can facilitateexchange of information and/or data within the imaging system 100 orbetween a component of the imaging system 100 and an external device. Insome embodiments, one or more components of the imaging system 100(e.g., the ECT scanner 110, the terminal 130, the processing engine 140,the storage 150, etc.) may exchange information and/or data with one ormore other components of the imaging system 100 via the network 120. Forexample, the processing engine 140 may receive image data from the ECTscanner 110 directly or via the network 120. As another example, theprocessing engine 140 may obtain user instructions from the terminal 130via the network 120.

The network 120 may be and/or include a public network (e.g., theInternet), a private network (e.g., a local area network (LAN), a widearea network (WAN)), etc.), a wired network (e.g., an Ethernet network),a wireless network (e.g., an 802.11 network, a Wi-Fi network, etc.), acellular network (e.g., a Long Term Evolution (LTE) network), a framerelay network, a virtual private network (“VPN”), a satellite network, atelephone network, routers, hubs, switches, server computers, and/or anycombination thereof. Merely by way of example, the network 120 mayinclude a cable network, a wireline network, a fiber-optic network, atelecommunications network, an intranet, a wireless local area network(WLAN), a metropolitan area network (MAN), a public telephone switchednetwork (PSTN), a Bluetooth™ network, a ZigBee™ network, a near fieldcommunication (NFC) network, or the like, or any combination thereof. Insome embodiments, the network 120 may include one or more network accesspoints. For example, the network 120 may include wired and/or wirelessnetwork access points such as base stations and/or internet exchangepoints through which one or more components of the ECT system 100 may beconnected to the network 120 to exchange data and/or information.

The terminal(s) 130 may include a mobile device 131, a tablet computer132, a laptop computer 133, or the like, or any combination thereof. Insome embodiments, the mobile device 131 may include a smart home device,a wearable device, a mobile device, a virtual reality device, anaugmented reality device, or the like, or any combination thereof.Exemplary smart home device may include a smart lighting device, acontrol device of an intelligent electrical apparatus, a smartmonitoring device, a smart television, a smart video camera, aninterphone, or the like, or any combination thereof. Exemplary wearabledevice may include a bracelet, a footgear, eyeglasses, a helmet, awatch, clothing, a backpack, a smart accessory, or the like, or anycombination thereof. Exemplary mobile device may include a mobile phone,a personal digital assistance (PDA), a gaming device, a navigationdevice, a point of sale (POS) device, a laptop, a tablet computer, adesktop, or the like, or any combination thereof. Exemplary virtualreality device and/or the augmented reality device may include a virtualreality helmet, virtual reality glasses, a virtual reality patch, anaugmented reality helmet, augmented reality glasses, an augmentedreality patch, or the like, or any combination thereof. For example, thevirtual reality device and/or the augmented reality device may include aGoogle Glass™, an Oculus Rift™, a Hololens™, a Gear VR™, etc. In someembodiments, the terminal(s) 130 may be implemented on the processingengine 140.

The processing engine 140 may process image data (e.g., raw scanningdata, a plurality of image slices) obtained from the ECT scanner 110,the terminal 130, and/or the storage 150. In some embodiments, theprocessing engine 140 may be a single server or a server group. Theserver group may be centralized or distributed. In some embodiments, theprocessing engine 140 may be local to or remote from other components inthe imaging system 100. The processing engine 140 may access ECT dataproduced by the ECT scanner 110, stored by the terminal 130, the storage150, an external storage device via, for example, the network 120.Alternatively, the processing engine 140 may be directly connected tothe ECT scanner 110, the terminal 130, and/or the storage 150 to accessthe image data. In some embodiments, the processing engine 140 may beimplemented on a cloud platform. Merely by way of example, the cloudplatform may include a private cloud, a public cloud, a hybrid cloud, acommunity cloud, a distributed cloud, an inter-cloud, a multi-cloud, orthe like, or any combination thereof. In some embodiments, theprocessing engine 140 may be implemented by a computing device havingone or more components as illustrated in FIG. 1-C.

The storage 150 may store data, instructions, and/or any otherinformation. In some embodiments, the storage 150 may store dataobtained from the terminal 130 and/or the processing engine 140. In someembodiments, the storage 150 may store data and/or instructions that theprocessing engine 140 may execute or use to perform exemplary methodsdescribed in the present disclosure.

In some embodiments, the storage 150 may include a mass storage, aremovable storage, a volatile read-and-write memory, a read-only memory(ROM), or the like, or any combination thereof. Exemplary mass storagemay include a magnetic disk, an optical disk, a solid-state drive, etc.Exemplary removable storage may include a flash drive, a floppy disk, anoptical disk, a memory card, a zip disk, a magnetic tape, etc. Exemplaryvolatile read-and-write memory may include a random access memory (RAM).Exemplary RAM may include a dynamic RAM (DRAM), a double date ratesynchronous dynamic RAM (DDR SDRAM), a static RAM (SRAM), a thyristorRAM (T-RAM), and a zero-capacitor RAM (Z-RAM), etc. Exemplary ROM mayinclude a mask ROM (MROM), a programmable ROM (PROM), an erasableprogrammable ROM (EPROM), an electrically erasable programmable ROM(EEPROM), a compact disk ROM (CD-ROM), and a digital versatile disk ROM,etc. In some embodiments, the storage 150 may be implemented on a cloudplatform. Merely by way of example, the cloud platform may include aprivate cloud, a public cloud, a hybrid cloud, a community cloud, adistributed cloud, an inter-cloud, a multi-cloud, or the like, or anycombination thereof.

In some embodiments, the storage 150 may be connected to the network 120to communicate with one or more other components in the imaging system100 (e.g., the processing engine 140, the terminal 130, etc.). One ormore components in the imaging system 100 may access the data orinstructions stored in the storage 150 via the network 120. In someembodiments, the storage 150 may be directly connected to or communicatewith one or more other components in the imaging system 100 (e.g., theprocessing engine 140, the terminal 130, etc.). In some embodiments, thestorage 150 may be part of the processing engine 140.

FIG. 1-B is a block diagram illustrating an exemplary processing engine140 according to some embodiments of the present disclosure. Asillustrated in FIG. 1-B, the processing engine 140 may include anacquisition module 141, a control module 142, a storage module 143, aprocessing module 144, and a display module 145.

The acquisition module 141 may acquire or receive ECT data. Merely byway of example with reference to a PET system, the acquisition module141 may acquire or receive PET data. For illustration purposes, during aPET scan or analysis, PET tracers (also referred to as “PET tracermolecules”) are first introduced into the subject before an imagingprocess begins. During the PET scan, the PET tracer molecules may emitpositrons, namely the antiparticles of electrons. A positron has thesame mass and the opposite electrical charge compared to an electron,and it undergoes an annihilation (also referred to as an “annihilationevent”) with an electron (that may naturally exist in abundance withinthe subject) as the two particles collide. An electron-positronannihilation may result in two 511 keV gamma photons, which, upon theirown generation, begin to travel in opposite directions with respect toone another. The line connecting the two gamma photons may be referredto as a line of response (LOR). The acquisition module 141 may obtainthe trajectory and/or information of the gamma photons. The PET data maybe used to determine a list of annihilation events, transverse andlongitudinal positions of the LORs, or the like, or a combinationthereof.

The control module 142 may generate a control parameter for controllingthe acquisition module 141, the storage module 143, the processingmodule 144, and/or the display module 145. For example, the controlmodule 142 may control the acquisition module 141 as to whether toacquire a signal, the time when a signal acquisition may occur, etc. Asanother example, the control module 142 may control the processingmodule 144 to select different algorithms to process the ECT data,acquire a motion signal (e.g., a respiratory motion signal), determineone or more symmetry related parameters of the motion signal, and/orcorrect the motion signal. In some embodiments, the control module 142may receive a real-time or a predetermined command provided by a user(e.g., a doctor) or the system 100 and control the acquisition module141, and/or the processing module 144 to acquire ECT data of a subjectaccording to the received command. In some embodiments, the controlmodule 142 may communicate with other modules in the processing engine140 for exchanging information or data.

The storage module 143 may store the acquired ECT data, the controlparameters, the processed ECT data, a motion signal derived from the ECTdata, a parameter related to the motion signal, or the like, or acombination thereof. In some embodiments, the storage module 143 mayinclude a mass storage, a removable storage, a volatile read-and-writememory, a read-only memory (ROM), or the like, or any combinationthereof. The mass storage may include a magnetic disk, an optical disk,a solid-state drives, etc. The removable storage may include a flashdrive, an optical disk, a memory card, a zip disk, a magnetic tape, etc.The volatile read-and-write memory may include a random access memory(RAM). The RAM may include a dynamic RAM (DRAM), a double date ratesynchronous dynamic RAM (DDR SDRAM), a static RAM (SRAM), a thyristorRAM (T-RAM), and a zero-capacitor RAM (Z-RAM), etc. The ROM may includea mask ROM (MROM), a programmable ROM (PROM), an erasable programmableROM (PEROM), an electrically erasable programmable ROM (EEPROM), acompact disk ROM (CD-ROM), and a digital versatile disk ROM, etc. Insome embodiments, the storage module 143 may store one or more programsand/or instructions that may be executed by one or more processors ofthe processing engine 140 (e.g., the processing module 144) to performexemplary techniques described in the disclosure. For example, thestorage module 143 may store program(s) and/or instruction(s) executedby the processor(s) of the processing engine 140 to acquire ECT data,acquire a respiratory motion signal via the ECT data, reconstruct animage based on the ECT data, or display any intermediate result or aresultant image.

The processing module 144 may process data received from one or moremodules in the processing engine 140. In some embodiments, theprocessing module 144 may process the ECT data acquired by theacquisition module 141, or retrieved from the storage module 143. Insome embodiments, the processing module 144 may extract a motion signalfrom the ECT data, reconstruct ECT images based on the ECT data,generate reports including one or more ECT images and/or other relatedinformation, determine whether the motion signal is flipped, correct therespiratory motion signal, or the like, or a combination thereof. Forexample, the processing module 144 may process the ECT data based on agating approach and reconstruct an ECT image based on the gated ECTdata. As another example, the processing module 144 may determine aplurality of gating parameters for the ECT data corresponding to aplurality of spatial points of the subject (e.g., chest, back, or thelike) based on the motion signal.

The display module 145 may display any information related to theprocessing engine 140. The information may include programs, software,algorithms, data, text, number, images, voice, or the like, or anycombination thereof. In some embodiments, the display module 145 mayinclude a liquid crystal display (LCD), a light emitting diode (LED)based display, a flat panel display, a cathode ray tube (CRT), a touchscreen, or the like, or a combination thereof. The touch screen mayinclude, for example, a resistance touch screen, a capacity touchscreen, a plasma touch screen, a vector pressure sensing touch screen,an infrared touch screen, or the like, or a combination thereof.

In some embodiments, one or more modules illustrated in FIG. 1-B may beimplemented in at least part of the exemplary imaging system 100illustrated in FIG. 1-A. The acquisition module 141, the control module142, the storage module 143, the processing module 144, and/or thedisplay module 145 may be integrated into a console. Via the console, auser may set parameters for scanning, control the imaging procedure,control a correcting procedure of a motion signal, control a parameterof the reconstruction of an image, view the motion signal, view thereconstructed images, etc. In some embodiments, the console may beimplemented in the computing device as illustrated in FIG. 1-C.

FIG. 1-C is a schematic diagram illustrating an exemplary computingdevice 160 on which the processing engine 140 may be implementedaccording to some embodiments of the present disclosure.

The computing device 160 may be a general purpose computer or a specialpurpose computer. Both may be used to implement the processing engine140 of the present disclosure. For example, the processing engine 140 ofthe imaging system 100 may be implemented on the computing device 160,via its hardware, software program, firmware, or a combination thereof.Although only one such computer is shown for convenience, the computerfunctions related to the imaging system 100 as described herein may beimplemented in a distributed manner on a number of similar platforms todistribute the processing load.

The computing device 160, for example, may include communication (COMM)ports 165 connected to and from a network (e.g., the network 120)connected thereto to facilitate data communications. The computingdevice 160 may also include a processor (e.g., a central processing unit(CPU)) 162, in the form of one or more processors, for executing programinstructions. The exemplary computer platform may include an internalcommunication bus 161, program storage and data storage of differentforms, for example, a disk 167, and a read only memory (ROM) 163, or arandom access memory (RAM) 164, for various data files to be processedand/or transmitted by the computer. The exemplary computer platform mayalso include program instructions stored in the ROM 163, the RAM 164,and/or other type of non-transitory storage medium to be executed by theprocessor 162. The methods and/or processes of the present disclosuremay be implemented as the program instructions. The computing device 160also includes an I/O component 166, supporting input/output between thecomputer and other components therein. The computing device 160 may alsoreceive programming and data via network communications.

Merely for illustration, only one processor is described in thecomputing device 160. However, it should be noted that the computingdevice 160 in the present disclosure may also include multipleprocessors, and thus operations that are performed by one processor asdescribed in the present disclosure may also be jointly or separatelyperformed by the multiple processors. For example, the processor of thecomputing device 160 executes both operation A and operation B. As inanother example, operation A and operation B may also be performed bytwo different processors jointly or separately in the computing device160 (e.g., the first processor executes operation A and the secondprocessor executes operation B, or the first and second processorsjointly execute operations A and B).

FIG. 1-D is a schematic diagram illustrating exemplary hardware and/orsoftware components of an exemplary mobile device 170 on which theterminal 130 may be implemented according to some embodiments of thepresent disclosure. As illustrated in FIG. 1-D, the mobile device 170may include a communication platform 171, a display 172, a graphicprocessing unit (GPU) 173, a central processing unit (CPU) 174, an I/O175, a memory 176, and a storage 179. In some embodiments, any othersuitable component, including but not limited to a system bus or acontroller (not shown), may also be included in the mobile device 170.In some embodiments, a mobile operating system 177 (e.g., iOS™, Android™Windows Phone™, etc.) and one or more applications 178 may be loadedinto the memory 176 from the storage 179 in order to be executed by theCPU 174. The applications 178 may include a browser or any othersuitable mobile apps for receiving and rendering information relating toimage processing or other information from the processing engine 140.User interactions with the information stream may be achieved via theI/O 175 and provided to the processing engine 140 and/or othercomponents of the imaging system 100 via the network 120.

To implement various modules, units, and their functionalities describedin the present disclosure, computer hardware platforms may be used asthe hardware platform(s) for one or more of the elements describedherein. A computer with user interface elements may be used to implementa personal computer (PC) or any other type of work station or terminaldevice. A computer may also act as a server if appropriately programmed.

FIG. 2 is a block diagram illustrating an exemplary processing module144 according to some embodiments of the present disclosure. Theprocessing module 144 may include a motion signal acquisition unit 202,a symmetry determination unit 204, a flip determination unit 206, and acorrection unit 208. In some embodiments, the units may be connectedwith each other via a wired connection (e.g., a metal cable, an opticalcable, a hybrid cable, or the like, or any combination thereof) or awireless connection (e.g., a Local Area Network (LAN), a Wide AreaNetwork (WAN), a Bluetooth, a ZigBee, a Near Field Communication (NFC),or the like, or a combination thereof). The processing module 144 may beimplemented on various components (e.g., the processor 162 of thecomputing device 160 as illustrated in FIG. 1-C). For example, at leasta portion of the processing module 144 may be implemented on thecomputing device 160 as illustrated in FIG. 1-C or the mobile device 170as illustrated in FIG. 1-D.

The motion signal acquisition unit 202 may acquire a motion signal. Themotion signal may reflect a motion state of a subject. For example, arespiratory motion signal may reflect the motion of a tissue or an organthat is influenced by the respiratory motion of a subject. A cardiacmotion signal may reflect the motion of the heart of a subject.

In some embodiments, the motion signal acquisition unit 202 may acquirethe motion signal through an external device that detects a motion ofthe subject or a portion of the subject. In some embodiments, the motionsignal acquisition unit 202 may acquire the motion signal based on ECTdata generated from a subject or a portion of the subject. For example,the motion signal acquisition unit 202 may extract the respiratorymotion signal from ECT data based on a data-driven technique. Exemplarydata-driven techniques may include an approach based on a center ofmass, an approach based on counts levels, an approach of a principalcomponent analysis, or the like, or any combination thereof. The motionsignal acquisition unit 202 may acquire the respiratory motion signalduring or after the scanning, and/or before image reconstruction.

The symmetry determination unit 204 may determine one or more values ofa symmetry related parameter of a motion signal. For illustrationpurposes, a respiratory motion signal, as shown in FIG. 11, is taken asan example. As shown in FIG. 11, the amplitude of the respiratory motionsignal changes over time. In some embodiments, the amplitude of therespiratory motion signal may correspond to the displacement of aportion of an organ along a specific direction, e.g., the directionperpendicular to the coronal plane of a subject (e.g., a patient). Insome embodiments, an ascending phase in the respiratory motion signalmay be referred to as a candidate inspiration phase, and a descendingphase in the respiratory motion signal may also be referred to as acandidate expiration phase. In some embodiments, the symmetry relatedparameter may be determined based on the asymmetry between thetransition from an ascending phase to a descending phase and thetransition from a descending phase to an ascending phase. For example,the transition from the ascending phase to the descending phase appearssharper than the transition from the descending phase to the ascendingphase in the respiratory motion signal as shown in FIG. 11. With respectto a respiratory motion signal, the value of a symmetry relatedparameter may include an off-center value of the respiratory motionsignal. The determination of the value of the symmetry related parametermay be found elsewhere in the disclosure. See, e.g., FIG. 4 and thedescription thereof.

The flip determination unit 206 may determine whether a motion signal isflipped. It should be noted to persons having ordinary skills in the artthat a motion signal with respect to a subject may be asynchronous tothe actual motion state of the subject. For illustration purposes, if arespiratory motion signal, e.g., as illustrated in FIG. 11, is flipped,an ascending phase of the respiratory motion signal may correspond to anexpiration phase of the actual motion state and a descending phase maycorrespond to an inspiration phase of the actual motion state.

In some embodiments, the flip determination unit 206 may determinewhether a respiratory motion signal is flipped based on one or morevalues of a symmetry related parameter. For example, the flipdetermination unit 206 may compare the one or more values of thesymmetry related parameter with a predetermined threshold. The flipdetermination unit 206 may determine whether the respiratory motionsignal is flipped based on the comparison.

Additionally or alternatively, the flip determination unit 206 maydetermine whether the respiratory motion signal is flipped based on aplurality of images. Each of the images may be reconstructed based onECT data acquired at a time point or within a time frame. For example,the flip determination unit 206 may determine the motion of a point ofinterest in a plurality of images. The flip determination unit 206 mayfurther determine whether the respiratory motion signal is flipped basedon the motion of the point of interest.

The correction unit 208 may correct a motion signal. In someembodiments, the correction unit 208 may flip a respiratory motionsignal if the respiratory motion signal is flipped. For example, thecorrection unit 208 may turn the respiratory motion signal upside downaccording to the reference line. Therefore, an ascending phase of thecorrected respiratory motion signal may correspond to an inspirationphase of the actual motion state and a descending phase of the correctedrespiratory motion signal may correspond to an expiration phase of theactual motion state.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skills in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure. For example, eachof the units in the processing module 144 may access to a storage mediumof the processing engine 140, or a storage medium external to theprocessing engine 140. As another example, the units may be partiallyintegrated into one or more independent units or share one or moresub-units.

FIG. 3 is a flowchart illustrating an exemplary process for correcting amotion signal according to some embodiments of the present disclosure.The operations of the process 300 presented herein are intended to beillustrative. In some embodiments, the process 300 may be accomplishedwith one or more additional operations not described, and/or without oneor more of the operations discussed. Additionally, the order in whichthe operations of the process as illustrated in FIG. 3 and describedbelow in not intended to be limiting. In some embodiments, one or moreoperations of process 300 illustrated in FIG. 3 for correcting a motionsignal may be implemented in the imaging system 100 illustrated in FIG.1-A. For example, the process 300 illustrated in FIG. 3 may be stored ina storage (e.g., the storage 150) in the form of instructions, andinvoked and/or executed by the processing engine 140 (e.g., theprocessor 162 of the computing device 160 as illustrated in FIG. 1-C,the GPU 173 or CPU 174 of the mobile device 170 as illustrated in FIG.1-D).

In 302, ECT data may be obtained. In some embodiments, the ECT data maybe obtained by the acquisition module 141. The acquisition module 141may acquire the ECT data when the ECT scanner 110 scans a subject or aportion of the subject. For example, the ECT data may includecoincidence events originating from a volume of interest (VOI) of apatient that undergoes a respiratory motion.

In 304, a motion signal may be determined based on the ECT data. In someembodiments, the motion signal may be determined by the motion signalacquisition unit 202. The motion signal may be determined based on theECT data via various techniques. For example, a coincidence countsversus time curve may be determined, thus providing an estimatedrespiratory motion signal. As another example, a center of mass of, forexample, a distribution of PET tracers inside a VOI may be derived fromthe ECT data. Then, a displacement of the center of mass as a functionof time may provide a respiratory motion signal. As a further example, aprincipal component analysis (PCA) may be applied to the listmode ECTdata. Then, a respiratory motion signal may be obtained as the principalcomponent weight factor whose frequency spectrum has the highest peakamong the frequency band of a respiratory motion.

The motion signal acquisition unit 202 may acquire the respiratorymotion signal during or after the scanning, and/or before an imagereconstruction process. Exemplary respiratory motion signals acquired bythe respiratory motion signal acquisition unit 202 may be foundelsewhere in the present disclosure. See, e.g., FIG. 11.

In 306, one or more values of a symmetry related parameter of the motionsignal may be determined. In some embodiments, the one or more values ofthe symmetry related parameter may be determined by the symmetrydetermination unit 204. For illustration purpose, the values of thesymmetry related parameter of a respiratory motion signal may correspondto an asymmetry between a transition from a candidate inspiration phaseto a candidate expiration phase and a transition from a candidateexpiration phase to a candidate inspiration phase in one or morerespiratory cycles.

In some embodiments, the value(s) of the symmetry related parameter maybe determined based on an end of a candidate inspiration phase (alsoreferred as a candidate EIP) and/or an end of a candidate expirationphase (also referred as a candidate EEP). As used herein, a candidateEIP may refer to an end of an ascending phase in the respiratory motionsignal, such as a crest of the respiratory motion signal as illustratedin FIG. 11. As used herein, a candidate EEP may refer to an end of adescending phase in the respiratory motion signal, such as a trough inthe respiratory motion signal as illustrated in FIG. 11.

A candidate EIP may be identified by determining a local maximum motionamplitude (or referred to as a local maximum for brevity) on therespiratory motion signal. A candidate EEP may be identified bydetermining a local minimum motion amplitude (or referred to as a localminimum for brevity) on the respiratory motion signal.

In some embodiments, the value(s) of the symmetry related parameter maybe determined based on a duration of the transition from a candidateinspiration phase to a candidate expiration phase (also referred to as“first transition”) and/or a duration of the transition from a candidateexpiration phase to a candidate inspiration phase (also referred to as“second transition”). The duration of the first transition or the secondtransition may be determined with respect to a reference line, e.g.,line α, β, or γ as illustrated in FIG. 11. Details regarding thereference line may be found elsewhere in the disclosure.

In some embodiments, the value(s) of the symmetry related parameter maybe determined according to one respiratory cycle (e.g., the respiratorycycle located between point A and point B as illustrated in FIG. 11). Insome embodiments, a respiratory motion signal with a duration of timethat is greater than a threshold, e.g., 100 seconds, may be used todetermine the value(s) of the symmetry related parameter. Multiplevalues of the symmetry related parameter may be determined according todifferent portions of the respiratory motion signal. For example, thedifferent portions of the respiratory motion signal may include a sametime interval. As another example, two different portions of therespiratory motion signal used to determine the value(s) of the symmetryrelated parameter do not overlap. As a further example, two differentportions of the respiratory motion signal may at least partiallyoverlap. For instance, the different portions of the respiratory motionsignal may have a same starting time point or different start timepoints, and a same end time point or different end time points.

In 308, whether the motion signal is flipped may be determined based onthe one or more values of the symmetry related parameter. In someembodiments, whether the motion signal is flipped may be determined bythe flip determination unit 206. In some embodiments, a respiratorymotion signal may be deemed flipped if a candidate EIP and a candidateEEP in the respiratory motion signal are flipped. In some embodiments, arespiratory motion signal may be deemed flipped if an ascending phase inthe respiratory motion signal and a descending phase in the respiratorymotion signal are flipped.

One or more conditions may be used in determining whether therespiratory motion signal is flipped. For example, the one or moreconditions may including comparing the one or more values of thesymmetry related parameter with a predetermined threshold. Alternativelyor additionally, the one or more conditions may include determiningcredibility of the one or more values of the symmetry related parameter,and then determining whether the respiratory motion signal is flippedbased on the credibility of the one or more values of the symmetryrelated parameter.

In 310, the motion signal may be corrected if the motion signal isflipped. In some embodiments, the correction of the respiratory motionsignal may be performed by the correction unit 208. In some embodiments,the correction of the respiratory motion signal may include flipping therespiratory motion signal, e.g., flipping the respiratory motion signalupside down. In some embodiments, “the respiratory motion signal isflipped” may refer to that every respiratory cycle, including acandidate EIP and a candidate EEP, is flipped. In some embodiments, “therespiratory motion signal is flipped” may refer to that part of therespiratory motion signal, including some of the respiratory cycles, areflipped.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skills in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure. In someembodiments, operation 302 may be omitted, and thus the motion signalmay be acquired by a device, e.g., a sensor. For example, a sensor(e.g., a pressure sensor, a motion sensor) may be used to collect datarelated to the displacement of the chest or abdominal wall of a subject.Based on the data collected by the sensor, the motion signal acquisitionunit 202 may derive a respiratory motion signal with respect to thesubject.

FIG. 4 is a flowchart illustrating an exemplary process for determiningone or more values of a symmetry related parameter of a motion signalaccording to some embodiments of the present disclosure. In someembodiments, the process 400 may be performed to achieve 306 asillustrated in FIG. 3. The operations of the process 400 presentedherein are intended to be illustrative. In some embodiments, the process400 may be accomplished with one or more additional operations notdescribed, and/or without one or more of the operations discussed.Additionally, the order in which the operations of the process asillustrated in FIG. 4 and described below in not intended to belimiting. In some embodiments, one or more operations of process 400illustrated in FIG. 4 for determining one or more symmetry relatedparameters of a motion signal may be implemented in the imaging system100 illustrated in FIG. 1-A. For example, the process 400 illustrated inFIG. 4 may be stored in a storage (e.g., the storage 150) in the form ofinstructions, and invoked and/or executed by the processing engine 140(e.g., the processor 162 of the computing device 160 as illustrated inFIG. 1-C, the GPU 173 or CPU 174 of the mobile device 170 as illustratedin FIG. 1-D).

In 402, a motion signal may be obtained. In some embodiments, the motionsignal may be acquired by the motion signal acquisition unit 202 asdescribed elsewhere in the present disclosure.

In 404, a reference line of the motion signal may be determined. In someembodiments, the determination of the reference line of the respiratorymotion signal may be performed by the symmetry determination unit 204.The reference line may separate the motion signal into two parts, afirst part above the reference line and a second part below thereference line. In some exemplary embodiments with respect to arespiratory motion signal, one or more candidate EIPs may be locatedabove the reference line, and one or more candidate EEPs may be locatedbelow the reference line. It should be appreciated that if therespiratory motion signal is not flipped, the candidate EIPs/EEPs may bedeemed as actual EIPs/EEPs with respect to the actual motion of asubject. If the respiratory motion signal is flipped, the candidate EIPsmay correspond to actual EEPs, the candidate EEPs may correspond toactual EIPs, and thus the respiratory motion signal may need to becorrected.

In some embodiments, the reference line may be determined based on anamplitude of a candidate EIP and an amplitude of a candidate EEP. Asused herein, an amplitude of a candidate EIP may be a first peakamplitude of the respiratory motion signal with respect to the referenceline, and an amplitude of a candidate EEP may be a first valleyamplitude of the respiratory motion signal with respect to the referenceline. For example, the reference line may be midway between thecandidate EIP and the candidate EEP such that the amplitude of thecandidate EIP is equal to the amplitude of the candidate EEP. Referringto FIG. 11 as an example, the reference line may be line α. Thecandidate EIP and candidate EEP between point M and point N may have asame amplitude with respect to the line α. Points M and N are where themotion signal intersects with the reference line α, and the motionsignal between M and N spans at least one cycle of the respiratorymotion of interest. In some embodiments, the candidate EIP and thecandidate EEP used to determine the reference line may occur within thesame cycle or in different cycles of the respiratory motion. In someembodiments, the first peak amplitude of the respiratory motion signalwith respect to the reference line may be an average peak amplitude of aplurality peaks in the respiratory motion signal. The first valleyamplitude of the respiratory motion signal with respect to the referenceline may be an average valley amplitude of a plurality valleys in therespiratory motion signal.

In some embodiments, the reference line may be determined based on aduration of a first transition of a respiratory motion signal and aduration of a second transition of the respiratory motion signal. Theduration of the first transition may refer to a time period includingpart of a candidate inspiration phase before a candidate EIP and part ofa candidate expiration phase after the candidate EIP. The duration ofthe second transition may refer to a time period including part of acandidate expiration phase before a candidate EEP and part of acandidate inspiration phase after the candidate EEP. For example, thereference line may be determined such that the duration of the firsttransition is equal to the duration of the second transition. Withreference to the reference line, the duration of the first transitionmay refer to a time period including part of a candidate inspirationphase before a candidate EIP and part of a candidate expiration phaseafter the candidate EIP, in which both parts are above the referenceline as illustrated in FIG. 11; the duration of the second transitionmay refer to a time period including part of a candidate expirationphase before a candidate EEP and part of a candidate inspiration phaseafter the candidate EEP, in which both parts are below the referenceline as illustrated in FIG. 11. Referring to FIG. 11 as an example, thereference line may be line β. The duration of the first transition,represented by the interval between point C and point D, is equal to theduration of the second transition, represented by the interval betweenpoint D′ and point E. Points C, D, D′, and E are where the motion signalintersects with the reference line β. In some embodiments, the durationof the first transition and the duration of the second transition usedto determine the reference line may occur in a same cycle of therespiratory motion; D and D′ may coincide with each other. In someembodiments, the duration of the first transition and the duration ofthe second transition used to determine the reference line may occur indifferent cycles of the respiratory motion; D and D′ are separate fromeach other.

In some embodiments, the reference line may be determined based on afirst criterion including a combination of an amplitude and a durationof a respiratory motion signal or part of the respiratory motion signal.For example, the first criterion may refer to that the area above thereference line (e.g., represented by an integration of the first part ofthe respiratory motion signal above the reference line) is equal to thearea below the reference line (e.g., represented by an integration ofthe second part of the respiratory motion signal below the referenceline). For illustration purposes, the motion amplitude corresponding tothe reference line may be determined as follows:

$\begin{matrix}{{R_{\gamma} = \frac{\int_{t_{1}}^{t_{2}}{{s(t)}{dt}}}{t_{2} - t_{1}}},} & (1)\end{matrix}$

where R_(γ) is the motion amplitude corresponding to the reference line,t₁ is a first time point of the respiratory motion signal, t₂ is asecond time point of the respiratory motion signal, s(t) is therespiratory motion signal acquired according to some embodiments of thepresent disclosure. The first time point may be the starting point ofthe respiratory motion signal. The second time point may be any timepoint, other than the first time point, of the respiratory motionsignal. In some embodiments, the interval between the first time pointand the second time point may be no less than a threshold, such as 100seconds.

In 406, a value of a symmetry related parameter may be determined basedon the reference line. In some embodiments, the determination of thevalue of the symmetry related parameter based on the reference line maybe performed by the symmetry determination unit 204.

In some embodiments with respect to a respiratory motion signal, thevalue of the symmetry related parameter may be determined in differentmanners if the reference line is determined in different manners.

Merely by way of example, if the reference line is determined on thebasis that an amplitude of a candidate EIP is equal to an amplitude of acandidate EEP, the value of the symmetry related parameter may bedetermined based on the duration of a first transition related to thecandidate EIP and the duration of a second transition related to thecandidate EEP. As described elsewhere in the present disclosure, withreference to the reference line, the duration of the first transitionmay refer to a time period including part of a candidate inspirationphase before a candidate EIP and part of a candidate expiration phaseafter the candidate EIP, in which both parts are above the referenceline as illustrated in FIG. 11; the duration of the second transitionmay refer to a time period including part of a candidate expirationphase before a candidate EEP and part of a candidate inspiration phaseafter the candidate EEP, in which both parts are below the referenceline as illustrated in FIG. 11. Then, the value of the symmetry relatedparameter D may be determined based on the following formula:

$\begin{matrix}{{D = \frac{T_{1}}{T_{2}}},} & (2)\end{matrix}$

where T₁ is the duration of the first transition related to thecandidate EIP, and T₂ is the duration of the second transition relatedto the candidate EEP.

Referring to FIG. 11 as an example, the reference line may be the lineα. The duration of the first transition related to the candidate EIP maybe represented by the interval between point M and point L. The durationof the second transition related to the candidate EEP may be representedby the interval between point L and point N. Points L, M, and N arewhere the motion signal intersects with the reference line α asillustrated in FIG. 11.

Merely by way of example, if the reference line is determined on thebasis that a duration of a first transition is equal to a duration of asecond transition, the value of the symmetry related parameter may bedetermined based on an amplitude of one or more candidate EIPs relatedto the first transition and/or an amplitude of one or more candidateEEPs related to the second transition. In some embodiments, the one ormore candidate EIPs related to the first transition may be identified ata local maximum during the first transition. The one or more candidateEEPs related to the second transition may be identified at a localminimum during the second transition. In some embodiments, the amplitudeof one or more candidate EIPs may be an average peak amplitude of theone or more candidate EIPs of the motion signal with respect to thereference line. The amplitude of one or more candidate EEPs may be anaverage valley amplitude of the one or more candidate EEPs of the motionsignal with respect to the reference line. Then, the value of thesymmetry related parameter D may be determined based on the followingformula:

$\begin{matrix}{{D = \frac{H_{{ma}\; x}}{H_{m\; i\; n}}},} & (3)\end{matrix}$

where H_(max) is the amplitude of one or more candidate EIPs related tothe first transition with respect to the reference line, and H_(min) isthe amplitude of one or more candidate EEPs with respect to the secondtransition with respect to the reference line.

Merely by way of example, if the reference line is determined based onthe first criterion as described according to formula (1), the value ofthe symmetry related parameter may be determined based on a secondcriterion that includes a combination of a weighted amplitude and aduration of the respiratory motion signal or part of the respiratorymotion signal. For illustration purposes, the value of the symmetryrelated parameter D in accordance to the second specific criterion maybe determined as follows:

$\begin{matrix}{{{s_{2}(t)} = {{s(t)} - R_{\gamma}}},} & (4) \\{{D = \frac{\int_{t_{1}}^{t_{2}}{{s_{2}(t)}{f\left( {{s_{2}(t)}} \right)}{dt}}}{t_{2} - t_{1}}},} & (5)\end{matrix}$

where t₁ and t₂ are the first and second time points as illustrated informula (1), s(t) is the respiratory motion signal that is acquiredaccording to some embodiments of the present disclosure, s₂(t) is asecond respiratory motion signal that is determined based on therespiratory signal s(t) and the reference line R_(γ) (the reference lineacquired according to the first criteria), |s₂(t)| is the absolute valueof the second respiratory motion signal, and f( ) is a mono-increasefunction. It shall be noted that the value of the symmetry relatedparameter D may indicate which part of the respiratory motion signal,the part above the reference line or the part below the reference line,appears sharper. In some embodiments, if the part above the referenceline appears sharper than the part below the reference line, the valueof the symmetry related parameter D may be positive. Likewise, if thepart below the reference line appears sharper than the part above thereference line, the value of the symmetry related parameter D may benegative.

The mono-increase function may include a polynomial function, anexponential function, a logarithmic function, or the like, or acombination thereof. For example, f( ) may be a polynomial, such as f()=x². Accordingly, the formula (5) may be converted to:

$\begin{matrix}{D = {\frac{\int_{t_{1}}^{t_{2}}{\left( {s_{2}(t)} \right)^{3}{dt}}}{t_{2} - t_{1}}.}} & (6)\end{matrix}$

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skills in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure. In someembodiments, only one symmetry related parameter may be determined basedon one reference line. In some embodiments, more than one symmetryrelated parameters may be determined based on one reference line.

FIG. 5 is a block diagram illustrating an exemplary flip determinationunit 206 according to some embodiments of the present disclosure. Theflip determination unit 206 may include a credibility determinationsub-unit 502, a gating sub-unit 504, a reconstruction sub-unit 506, animage registration sub-unit 508, a motion determination sub-unit 510,and a flip determination sub-unit 512. The flip determination unit 206may be implemented on various components (e.g., the processor 162 of thecomputing device 160 as illustrated in FIG. 1-C). For example, at leasta portion of the flip determination unit 206 may be implemented on thecomputing device 160 as illustrated in FIG. 1-C or the mobile device 170as illustrated in FIG. 1-D.

The credibility determination sub-unit 502 may determine the credibilityof one or more values of a symmetry related parameter of a motionsignal. The credibility of the one or more values of the symmetryrelated parameter may be determined according to various conditions,including a duration of the motion signal, a value(s) of the symmetryrelated parameter, the noise with respect to the motion signal, or thelike, or a combination thereof. Details regarding the credibility of thevalue(s) of the symmetry related parameter may be found elsewhere in thepresent disclosure. See, for example, FIG. 9 and the descriptionthereof.

The gating sub-unit 504 may gate ECT data related to a subject. As usedherein, “gating” may refer to the operation in which ECT data may beclassified into a plurality of frames (also referred to as “gated data”)corresponding to a plurality of time intervals or motion phases. Forexample, the ECT data may be gated based on the motion phases of arespiratory motion signal derived from the ECT data. The gating sub-unit504 may divide the respiratory motion signal into a plurality ofsections or phases. Each of the plurality of sections or phases maycorrespond to a same frame of gate ECT data.

Merely by way of example, the ECT data may be divided into two frames.One of the frames may correspond to, for example, the first part of arespiratory motion signal that is above a reference line. The otherframe may correspond to, for example, the second part of the respiratorymotion signal that is below the reference line. In some embodiments, thegated data may be processed to reconstruct images corresponding todifferent time intervals that relate to a motion of a subject.

The reconstruction sub-unit 506 may reconstruct an image. In someembodiments, the reconstruction sub-unit 506 may include amicrocontroller, a reduced instruction set computer (RISC), applicationspecific integrated circuits (ASICs), an application-specificinstruction-set processor (ASIP), a central processing unit (CPU), agraphics processing unit (GPU), a physics processing unit (PPU), amicrocontroller unit, a digital signal processor (DSP), a fieldprogrammable gate array (FPGA), an acorn reduced instruction setcomputing (RISC) machine (ARM), or any other circuit or processorcapable of executing the functions described herein, or the like, or acombination thereof. In some embodiments, the reconstruction sub-unit506 may use different reconstruction algorithms including an analyticreconstruction algorithm or an iterative reconstruction algorithm forimage reconstruction.

Exemplary analytic reconstruction algorithms may include a filter backprojection (FBP) algorithm, a back projection filter (BFP) algorithm, ap-filtered layer gram, or the like, or a combination thereof. Exemplaryiterative reconstruction algorithms may include a Maximum LikelihoodExpectation Maximization (ML-EM), an Ordered Subset ExpectationMaximization (OSEM), a Row-Action Maximum Likelihood Algorithm (RAMLA),a Dynamic Row-Action Maximum Likelihood Algorithm (DRAMA), or the like,or a combination thereof. In some embodiments, the reconstructionsub-unit 506 may reconstruct images based on the gated ECT datagenerated by the gating sub-unit 504.

The image registration sub-unit 508 may perform an image registration ofa plurality of images. In some embodiments, the image registrationsub-unit 508 may perform a registration of two or more images in adirection, e.g., in the z direction. As used herein, the z direction mayrepresent a direction that is perpendicular to the transverse plane of asubject (i.e., the direction from head to feet of a patient).

The motion determination sub-unit 510 may determine a motion trend of asubject. In some embodiments, the motion determination sub-unit 510 maydetermine the motion trend of the subject by determining the motion of apoint of interest within the subject. For example, the motion of thepoint of interest along a specific direction (e.g., the z direction) maybe determined to represent the motion trend of the subject. In someembodiments, the motion trend of the subject may be determined based ona registration of two images of the subject corresponding to differenttime intervals.

The flip determination sub-unit 512 may determine whether a motionsignal is flipped. In some embodiments, the flip determination sub-unit512 may determine whether a respiratory motion signal is flipped basedon one or more values of a symmetry related parameter with respect tothe respiratory motion signal. In some embodiments, the flipdetermination sub-unit 512 may determine whether a respiratory motionsignal is flipped based on the motion trend of a subject, details ofwhich may be found elsewhere in the disclosure.

It should be noted that the above description is merely provided for thepurpose of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skills in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure. For example, eachof the sub-units in the flip determination unit 206 may access to astorage medium of the processing engine 140, or a storage mediumexternal to the processing engine 140. As another example, the sub-unitsmay be partially integrated into one or more independent sub-units orshare one or more blocks.

FIG. 6 is a flowchart illustrating an exemplary process for determiningwhether a respiratory motion signal is flipped according to someembodiments of the present disclosure. In some embodiments, the process600 may be performed to achieve 308 as illustrated in FIG. 3. Theoperations of the process 600 presented herein are intended to beillustrative. In some embodiments, the process 600 may be accomplishedwith one or more additional operations not described, and/or without oneor more of the operations discussed. Additionally, the order in whichthe operations of the process as illustrated in FIG. 6 and describedbelow in not intended to be limiting. In some embodiments, one or moreoperations of process 600 illustrated in FIG. 6 for determining whethera respiratory motion signal is flipped may be implemented in the imagingsystem 100 illustrated in FIG. 1-A. For example, the process 600illustrated in FIG. 6 may be stored in a storage (e.g., the storage 150)in the form of instructions, and invoked and/or executed by theprocessing engine 140 (e.g., the processor 162 of the computing device160 as illustrated in FIG. 1-C, the GPU 173 or CPU 174 of the mobiledevice 170 as illustrated in FIG. 1-D).

In 602, one or more values of a symmetry related parameter of a motionsignal may be obtained. In some embodiments, the one or more values ofthe symmetry related parameter of the motion signal may be determined bythe symmetry determination unit 204 as described elsewhere in thedisclosure.

In 604, a credibility of the one or more values of the symmetry relatedparameter may be determined. In some embodiments, the credibility of theone or more values of the symmetry related parameter may be determinedby the credibility determination sub-unit 502. The credibility of theone or more values of the symmetry related parameter may be determinedaccording to various conditions, including a duration of the motionsignal, value(s) of the symmetry related parameter, a noise with respectto the motion signal, or the like, or a combination thereof. Detailsregarding determination of the credibility of the one or more values ofthe symmetry related parameter may be found elsewhere in the disclosure.See, e.g., FIG. 10 and the description thereof.

In 606, if the one or more values of the symmetry related parameter aredetermined as credible, the process 600 may proceed to 608. If the oneor more values of the symmetry related parameter are determined asincredible, the process 600 may proceed to Node A. Description regardingNode A may be found in, for example, FIG. 7.

In 608, whether the motion signal is flipped may be determined based onthe one or more values of the symmetry related parameter. In someembodiments, the determination of whether the motion signal is flippedmay be performed by the flip determination sub-unit 512. In someembodiments, the determination as to whether the motion signal isflipped based on the one or more values of the symmetry relatedparameter may include comparing the one or more values of the symmetryrelated parameter with a threshold, and determining whether the motionsignal is flipped based on the comparison. The threshold may bedetermined by the symmetry determination unit 204, or may be determinedby a user through the control module 142.

In some embodiments, the determination of whether a respiratory motionsignal is flipped may be based on an observation that a respiratorymotion signal is asymmetric. For instance, the transition of arespiratory motion signal related to an actual EIP appears sharper thanthe transition of the respiratory motion signal related to an actualEEP. See, e.g., FIG. 11.

Merely by way of example with respect to the respiratory motion asdescribed in connection with FIG. 4, if a value of the symmetry relatedparameter as illustrated in formula (2) is greater than 1 (i.e., D>1),it may indicate that the first transition related to the candidate EIPis sharper than the second transition related to the candidate EEP.Therefore, the actual EIP may correspond to the candidate EIP.Otherwise, if a value of the symmetry related parameter as illustratedin formula (2) is less than 1 (i.e., D<1), it may indicate that thesecond transition related to the candidate EEP is sharper than the firsttransition related to the candidate EIP. Therefore, the actual EIP maybe inconsistent with the candidate EIP, and thus the respiratory motionsignal is determined as flipped.

Merely by way of example with respect to the respiratory motion asdescribed in connection with FIG. 4, if a value of the symmetry relatedparameter as illustrated in formula (3) is greater than 1 (i.e., D>1),it may denote that the first transition related to the candidate EIP issharper than the second transition related to the candidate EEP.Therefore, the actual EIP may be consistent with the candidate EIP.Otherwise, if a value of the symmetry related parameter as illustratedin formula (3) is less than 1 (i.e., D<1), it may denote that the secondtransition related to the candidate EEP is sharper than the firsttransition related to the candidate EIP. Therefore, the actual EIP maybe inconsistent with the candidate EIP, and thus the respiratory motionsignal is determined as flipped.

Merely by way of example with respect to the respiratory motion signalas described in connection with FIG. 4, if a value of the symmetryrelated parameter as illustrated in formula (5) is positive (i.e., D>0),it may denote that the part where the fourth respiratory motion signalis greater than zero (s₂(t)>0) (or the part where the respiratory motionsignal s(t) is related to the candidate EIP that is above the referenceline R_(γ)) appears shaper than the part where the fourth respiratorymotion signal is less than zero (s₂(t)<0) (or the part where therespiratory motion signal s(t) is related to the candidate EEP that isbelow the reference line R_(γ)). Therefore, the actual EIP may beconsistent with the candidate EIP. Otherwise, if a value of the symmetryrelated parameters as illustrated in formula (5) is negative (i.e.,D<0), it may denote that the part where the fourth respiratory motionsignal is less than zero (s₂(t)<0) appears shaper than the part wherethe fourth respiratory motion signal is greater than zero (s₂(t)>0).Therefore, the actual EIP may be inconsistent with the candidate EIP,and thus the respiratory motion signal is determined as flipped.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skills in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure. For instance,operations 604 and 606 may be omitted and the flip determinationsub-unit 512 may determine whether the motion signal is flipped based onthe one or more values of the symmetry related parameter directly.

FIG. 7 is a flowchart illustrating an exemplary process of determiningwhether a motion signal is flipped according to some embodiments of thepresent disclosure. The process 700 may be performed when the process600 proceeds to Node A as described in FIG. 6. The operations of theprocess 700 presented herein are intended to be illustrative. In someembodiments, the process 700 may be accomplished with one or moreadditional operations not described, and/or without one or more of theoperations discussed. Additionally, the order in which the operations ofthe process as illustrated in FIG. 7 and described below in not intendedto be limiting. In some embodiments, one or more operations of process700 illustrated in FIG. 7 for determining whether a respiratory motionsignal is flipped may be implemented in the imaging system 100illustrated in FIG. 1-A. For example, the process 700 illustrated inFIG. 7 may be stored in a storage (e.g., the storage 150) in the form ofinstructions, and invoked and/or executed by the processing engine 140(e.g., the processor 162 of the computing device 160 as illustrated inFIG. 1-C, the GPU 173 or CPU 174 of the mobile device 170 as illustratedin FIG. 1-D).

In 702, ECT data may be gated based on the motion signal. The gating maybe performed by the gating sub-unit 504. The gating may include dividingthe ECT data into a plurality of frames, each of which may has asequence number, such as, for example, a first frame of ECT data, asecond frame of ECT data . . . , a nth frame of ECT data. Each of theplurality of frames may correspond to a time interval of a section ofthe motion signal. The gating may be performed based on, for example,the amplitude of the motion signal, or the phase of the motion signal.Details regarding the gating of the ECT data may be found in FIG. 8 andthe description thereof.

In 704, a plurality of images may be reconstructed based on the gatedECT data. In some embodiments, the reconstruction may be performed bythe reconstruction sub-unit 506. One or more frames of the ECT data maybe used to reconstruct an image corresponding to a motion-related stateof a subject. For example, an inspiration-phase image may bereconstructed based on a frame of the ECT data in an inspiratory phase,and an expiration-phase image may be reconstructed based on a frame ofthe ECT data in an expiratory phase. The reconstruction sub-unit 506 mayexecute a reconstruction algorithm to reconstruct an image based on oneor more frames of the ECT data, as described elsewhere in the presentdisclosure.

In 706, at least two of the plurality of images may be registered. Insome embodiments, the registration of the at least two of the pluralityof images may be performed by the image registration sub-unit 508. Theregistration of the at least two of the plurality of images may beperformed to assess the difference between the at least two of theplurality of images due at least partially to the differences in motionphase of the images. Exemplary differences may include a displacement ofa point of interest between two images, a deformation of a volume ofinterest between two images.

For illustration purposes, let F(x, y, z, g) represent a characteristicor feature of a reconstructed image, where g represents the sequencenumber of a frame (e.g., g=1, 2 . . . n), and (x, y, z) represents thecoordinate of a point (e.g., a voxel, a pixel) in the reconstructedimage. As used herein, the z axis is along the z direction as describedelsewhere in the disclosure, and the x axis and y axis form an x-y planethat is perpendicular to the z axis. Exemplary characteristics orfeatures of a reconstructed image may include a gray level of apixel/voxel, a mean gray level, a texture, a color, a contrast, abrightness, or the like, or any combination thereof. In someembodiments, the registration of the at least two of the images may beperformed in a specific direction. For example, a first imagereconstructed based on the first frame of the ECT data and an ith imagereconstructed based on the ith frame of the ECT data (i=2, 3 . . . , n)may be registered in the z direction. In some embodiments, variousapproaches may be used for image registration.

For example, a sum square error (SSE) based approach is used as anexample in the following:

SSE(m(z))=∫_(All)(F(x, y, z, i)−F(x, y, z+m(z), 1))² dz,   (7)

where m(z) denotes a displacement vector that represents a displacementof a point represented by (x, y, z) between a first image reconstructedbased on the first frame of the ECT data and ith image reconstructedbased on the ith frame of the ECT data. The integration is performedbased on all possible z values in the first image or the ith image.

In some embodiments, the first image and the ith image may be registeredsuch that the deviation parameter achieves a minimum value. Therefore,the displacement vector m(z) may be determined as follows:

$\begin{matrix}{{m(z)} = {\underset{m{(z)}}{argmin}\; {{{SSE}\left( {m(z)} \right)}.}}} & (8)\end{matrix}$

Various approaches may be used to solve the equation (8). Forillustration purposes, a Newton's method is described. The Newton'smethod include determining the displacement vector m(z) in a pluralityof iterations.

Firstly, an initial value for the displacement vector m(z) is assigned.For example, the initial value of the displacement vector m(z) may beassigned as 0. Then, the gradient of the deviation parameter SSE(m(z))is determined as:

$\begin{matrix}{{{g\left( {m(z)} \right)} = \frac{d\left( {{SSE}\left( {m(z)} \right)} \right)}{d\left( {m(z)} \right)}},} & (9)\end{matrix}$

where g(m(z)) denotes a derivative of the deviation parameter SSE(m(z))of the displacement vector m(z), representing a sensitivity to change ofthe deviation parameter with respect to a change of the displacementvector.

Furthermore, a second derivative H(m(z)) of the deviation parameterSSE(m(z)) of the displacement vector m(z) is determined as:

$\begin{matrix}{{H\left( {m(z)} \right)} = {\frac{d\; {g\left( {m(z)} \right)}}{d\left( {m(z)} \right)}.}} & (10)\end{matrix}$

Next, a new displacement vector m^(new)(z) may be updated based on thedisplacement vector m(z) in the previous iteration:

$\begin{matrix}{{m^{new}(z)} = {{m(z)} - {\frac{g\left( {m(z)} \right)}{H\left( {m(z)} \right)}.}}} & (11)\end{matrix}$

By way of iterations, the displacement vector m(z) may be updated untila termination condition is satisfied. Exemplary termination conditionmay include that a certain number of iterations have been performedand/or the difference between two displacement vectors determined in twosuccessive iterations is smaller than a threshold. In some embodiments,only one iteration is performed for determining the displacement vector.

In 708, a motion of a point of interest may be determined based on theregistration. In some embodiments, the motion may be determined by themotion determination sub-unit 510. The motion may refer to a directionof movement along a specific direction (e.g., the z direction) of apoint of interest and/or the magnitude of the motion.

Merely by way of example, the motion of the point of interest may bedetermined based on the registration of the first image reconstructedbased on the first frame of the ECT data and the ith image reconstructedbased on the ith frame of the ECT data. A weighted displacement vectormay be acquired by combining the characteristic or feature (e.g., thegray value) of the pixel/voxel with the displacement vector m(z):

w(z)=m(z)*F(x, y, z, 1),   (12)

where w(z) represents the weighted displacement vector.

The motion T(x, y) of at point (x, y) may be determined as follows:

T(x, y)=∫_(All) w(z)dz.   (13)

In some embodiments, the point of interest may refer to the point withthe largest motion (e.g., the maximum absolute value of the motion) asdescribed below:

$\begin{matrix}{{\left( {x_{m},y_{m}} \right) = {\underset{({x,y})}{\arg \; \max}{{T\left( {x,y} \right)}}}},} & (14)\end{matrix}$

where (x_(m), y_(m)) is the point of interest.

The motion T of the point of interest from the first image to the ithimage may be determined as:

T=T(x _(m) , y _(m)).   (15)

In some embodiments, the motion of the point of interest may bedetermined based on the registration of any two image, e.g., the nthimage reconstructed based on the nth frame of the ECT data and the mthimage reconstructed based on the mth frame of the ECT data. In someembodiments, different motions of point (x, y) may be determined basedon more than one registration. The registrations may include theregistration between the mth image reconstructed based the mth frame ofthe ECT data and the ith image reconstructed based on the ith frame ofthe ECT data, where m, i may denote any sequence number of a frame ofthe ECT data. And the different motions of point (x, y) may be combinedto determine the motion of a point of interest. For example, acombination of various motions of a point may be determined as:

T′=Σ_(j=1) ^(n−1) T _(j))(x, y),   (16)

where T′ represents the combination of various motions of point (x, y).

In some embodiments, if the ECT data are gated based on a plurality ofdurations of the respiratory motion signal, as described elsewhere inthe present disclosure, the motion of the point of interest in imageF(x, y, z, 1) may be determined based on the registration between imageF(x, y, z, 1) and image F(x, y, z, [i/2]), where [ ] used hereinrepresents a function of rounding.

In 710, a determination may be made as to whether the motion signal isflipped based on the motion of the point of interest. In someembodiments, the determination of whether the motion signal is flippedmay be performed by the flip determination sub-unit 512.

For illustration purposes, a respiratory motion signal is taken as anexample. If the motion of the point of interest as shown in formula (15)is positive, it may indicate that that motion of the point of interestis along the z direction from the head to the feet of a subject. Thesection of a respiratory motion signal corresponding to the first frameof ECT data (also referred to as “first section of the respiratorymotion signal”) may be closer to an actual EIP than the section of therespiratory motion signal corresponding to the ith frame of ECT data(also referred to as “ith section of the respiratory motion signal”). Ifthe motion of the point of interest as shown in formula (15) isnegative, it may indicate that the motion of the point of interest isalong the direction from the feet to the head of a patient. The ithsection of the respiratory motion signal may be closer to an actual EIPthan the first section of the respiratory motion signal. Then, in orderto determine whether the respiratory motion signal is flipped, theposition of the first section of the respiratory motion signal and theposition of the ith section of the respiratory motion signal may becompared.

If the first section of the respiratory motion signal is closer to acandidate EIP than the ith section of the respiratory motion signal, therespiratory motion signal may be determined as synchronous with theactual motion phase of the subject, and thus the respiratory motionsignal is determined as correct. If the ith section of the respiratorymotion signal is closer to a candidate EIP than the first section of therespiratory motion signal, the respiratory motion signal may bedetermined as asynchronous to the actual motion phase of the subject,and thus the respiratory motion signal is determined as flipped.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skills in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure. For example, thedetermination of whether the motion signal is flipped may be performedbased on the motion trend of a point of interest between any tworeconstructed images, under the condition that the sections of themotion signal with respect to the two reconstructed images aredetermined.

FIG. 8 is a flowchart illustrating an exemplary process for gating theECT data according to some embodiments of the present disclosure. Theprocess 800 may be performed by the gating sub-unit 504. In someembodiments, the process 800 may be performed to achieve 702 asillustrated in FIG. 7. The operations of the process 800 presentedherein are intended to be illustrative. In some embodiments, the process800 may be accomplished with one or more additional operations notdescribed, and/or without one or more of the operations discussed.Additionally, the order in which the operations of the process asillustrated in FIG. 8 and described below in not intended to belimiting. In some embodiments, one or more operations of process 800illustrated in FIG. 8 for gating the ECT data may be implemented in theimaging system 100 illustrated in FIG. 1-A. For example, the process 800illustrated in FIG. 8 may be stored in a storage (e.g., the storage 150)in the form of instructions, and invoked and/or executed by theprocessing engine 140 (e.g., the processor 162 of the computing device160 as illustrated in FIG. 1-C, the GPU 173 or CPU 174 of the mobiledevice 170 as illustrated in FIG. 1-D).

In 802, ECT data and a motion signal based on the ECT data may beobtained. In some embodiments, the ECT data may be acquired by theacquisition module 141, and the motion signal of the ECT data may beacquired by the processing module 144, as described elsewhere in thepresent disclosure. In some embodiments, the ECT data and/or the motionsignal of the ECT data may be retrieved from a storage device including,e.g., the storage 150, storage module 143, disk 167 and storage 179, anexternal storage device accessible by the system 100 or a portionthereof via, for example, the network 120, etc.

In 804, the motion signal may be divided into a plurality of sections.In some embodiments, the motion signal may be divided by the gatingsub-unit 504. In some embodiments, the motion signal may be divided intoa plurality of sections based on the amplitude of the motion signal, thedistribution of coincidence events, or the motion phases of the motionsignal.

For example, as shown in FIG. 12, a respiratory motion signal may bedivided into a first plurality of sections on the basis of the motionamplitude and also that each section of the respiratory motion signalcorresponds to a same number of coincidence events. A section of therespiratory motion signal may include separate portions of therespiratory motion signal between two adjacent dashed lines. Theamplitude interval of each of the first plurality of sections may bedifferent.

As another example, as shown in FIG. 13, a respiratory motion signal maybe divided into a second plurality of sections on the basis that eachsection of the respiratory motion signal corresponds to a same amplitudeinterval. A section of the respiratory motion signal may includeseparate portions of the respiratory motion signal between two adjacentdashed lines. The number of coincidence events corresponding to each ofthe second plurality of sections may be different.

As a further example, as shown in FIG. 14, a respiratory motion signalmay be divided into a third plurality of sections on the basis that eachsection of the respiratory motion signal corresponds to a same ordifferent time intervals. In some embodiments, the third plurality ofsections may be divided evenly during one respiratory cycle of therespiratory motion signal as shown in FIG. 14. In some embodiments, morethan one respiratory cycle may be divided into a plurality ofsub-sections, where each of the respiratory cycles may be dividedsimilarly. A section of the third plurality of sections may include asub-section in a same respiratory cycle or corresponding sub-sections indifferent respiratory cycles.

In 806, the ECT data may be gated based on the plurality of sections. Insome embodiments, a section of the plurality of sections (e.g., thefirst plurality of sections, the second plurality of sections, or thethird plurality of sections) of the motion signal may correspond to arange of time. The range of time may include a continuous time interval,or different discrete time intervals. The ECT data may be gated into aplurality of frames based on the plurality of sections such that a frameof ECT data may include coincidence events occurred in a same range oftime.

FIG. 9 is a block diagram illustrating exemplary credibilitydetermination sub-unit 502 according to some embodiments of the presentdisclosure. The credibility determination sub-unit 502 may include asymmetry related parameter comparison block 902, a duration comparisonblock 904, a variation determination block 906, and a noise comparisonblock 908. The credibility determination sub-unit 502 may be implementedon various components (e.g., the processor 162 of the computing device160 as illustrated in FIG. 1-C). For example, at least a portion of thecredibility determination sub-unit 502 may be implemented on thecomputing device 160 as illustrated in FIG. 1-C or the mobile device 170as illustrated in FIG. 1-D.

The credibility determination sub-unit 502 may determine the credibilityof one or more values of a symmetry related parameter of a motionsignal, as discussed elsewhere in the disclosure. In some embodiments,the credibility determination sub-unit 502 may obtain the motion signal,the one or more values of the symmetry related parameter from othermodules and/or units of the processing engine 140, such as, the motionsignal acquisition unit 202, and/or the symmetry related parameterdetermination unit 204. In some embodiments, the credibilitydetermination sub-unit 502 may retrieve the motion signal, and/or theone or more values of the symmetry related parameter from may beretrieved from a storage device including, e.g., the storage 150,storage module 143, disk 167 and storage 179, an external storage deviceaccessible by the system 100 or a portion thereof via, for example, thenetwork 120, etc.

The symmetry related parameter comparison block 902 may compare one ormore values of a symmetry related parameter with a first threshold. Insome embodiments, the first threshold may relate to a value of thesymmetry related parameter of the motion signal to assess symmetry orasymmetry of the motion signal with respect to a reference line. Itshould be noted for persons having ordinary skills in the art that theone or more values of the symmetry related parameter may relate to theasymmetry of the motion signal. The more asymmetrical the motion signalis, the greater the difference between the value(s) of the symmetryrelated parameter and the first threshold.

The duration comparison block 904 may compare a duration of the motionsignal with a second threshold. In some embodiments, the duration of arespiratory motion signal may include a duration of the motion signalused to determine the value of the symmetry related parameter (e.g.,t₂−t₁ in formula (5) or (6)). It should be noted for persons havingordinary skills in the art that the duration of the respiratory motionsignal used to determine the value(s) of the symmetry related parametershould be long enough in order to reduce the effect of an incompleterespiratory cycle and/or insufficient information used in thedetermination of the value(s) of the symmetry related parameter. Thesecond threshold may be selected based on the rhythm of the motionrepresented by the motion signal. For instance, for a cyclic motion(e.g., respiratory motion, cardiac motion, etc.), the second thresholdmay be at least 100%, or 120%, or 150%, or 180%, or 200%, etc., of theperiod (the duration of the time of one cycle) of the cyclic motion. Insome embodiments, the period may be measured before or when the ECT dataare acquired. In some embodiments, the period may be set based onempirical data by the system 100 or provided by a user (e.g., a doctor).For a same subject at different times, or for different subjects, theperiod or the suitable threshold may be the same or different, dependingon various factors of the subject(s). Merely by way of example, thesecond threshold may be 100 seconds with respect to respiratory motion.The second threshold may be determined by a user through the console orthe one or more terminals 130, or by the imaging system 100.

The variation determination block 906 may determine a variation of a setof values of a symmetry related parameter. The variation of the valuesmay represent the consistency of the values of the symmetry relatedparameter. The variation of the set of values of the symmetry relatedparameter may be determined by comparing the set of values with athreshold or with each other. For example, as described elsewhere in thepresent disclosure, the threshold may be 0 in the situation that the setof values of the symmetry related parameter are determined based onformula (6) or (7). The variation determination block 906 may compareeach of the set of values with 0. The one or more values of the symmetryrelated parameter may be determined as sufficiently consistent in thecase that the set of values of the symmetry related parameter arepositive or negative. Otherwise, the one or more values of the symmetryrelated parameter may be determined as inconsistent.

The noise comparison block 908 may determine a signal to noise ratio(SNR) of the motion signal and compare the SNR with a third threshold.The SNR may refer to the energy of signal over energy of noise inFourier domain. Details regarding the determination of the SNR may befound in “Real-Time Data-Driven Respiratory Gating with OptimizedAutomatic VOI Selection,” Nuclear Science Symposium and Medical ImagingConference (NSS/MIC), 2016 IEEE, 2016, the contents of which areincorporated herein by reference to its entirety. The third thresholdmay be determined by a user through the console or the one or moreterminals 130, or by the imaging system 100.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skills in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure. For example, anyblocks of the credibility determination sub-unit 502 may be removed orsome blocks may be partially integrated in one or more independentblocks.

FIG. 10 is a flowchart illustrating an exemplary process for determiningcredibility of one or more values of a symmetry related parameteraccording to some embodiments of the present disclosure. The process1000 may be performed by the credibility determination sub-unit 502. Insome embodiments, the credibility of the one or more symmetry relatedparameters as illustrated in 604 in FIG. 6 may be determined accordingto the process 1000. The operations of the process 1000 presented hereinare intended to be illustrative. In some embodiments, the process 1000may be accomplished with one or more additional operations notdescribed, and/or without one or more of the operations discussed.Additionally, the order in which the operations of the process asillustrated in FIG. 10 and described below in not intended to belimiting. In some embodiments, one or more operations of process 1000illustrated in FIG. 10 for determining credibility of one or more valuesof a symmetry related parameter may be implemented in the imaging system100 illustrated in FIG. 1-A. For example, the process 1000 illustratedin FIG. 10 may be stored in a storage (e.g., the storage 150) in theform of instructions, and invoked and/or executed by the processingengine 140 (e.g., the processor 162 of the computing device 160 asillustrated in FIG. 1-C, the GPU 173 or CPU 174 of the mobile device 170as illustrated in FIG. 1-D).

In 1002, a motion signal and one or more values of a symmetry relatedparameter of the motion signal may be obtained. In some embodiments, thecredibility determination sub-unit 502 may obtain a respiratory motionsignal from the motion signal acquisition unit 202, and one or morevalues of the symmetry related parameter of the respiratory motionsignal from the symmetry determination unit 204. In some embodiments,the credibility determination sub-unit 502 may retrieve the motionsignal, and/or the one or more values of the symmetry related parameterfrom may be retrieved from a storage device including, e.g., the storage150, storage module 143, disk 167 and storage 179, an external storagedevice accessible by the system 100 or a portion thereof via, forexample, the network 120, etc.

In 1004, a determination may be made as to whether the one or morevalues of the symmetry related parameter are below a first threshold. Insome embodiments, the determination may be made by the symmetry relatedparameter comparison block 902.

For illustration purposes, the symmetry related parameter comparisonblock 902 may compare the absolute value of each of the one or morevalues of the symmetry related parameter as illustrated in formula (6)with the first threshold. If the one or more values of the symmetryrelated parameter are below the first threshold, then the process 1000may proceed to 1014; otherwise, the process 1000 may proceed to 1006. Insome embodiments, the first threshold may be determined by a userthrough the one or more terminals 130. In some embodiments, the firstthreshold may be determined by the imaging system 100 based on, forexample, empirical data, a default setting of the system 100, etc.

In 1006, a determination may be made as to whether a duration of themotion signal is less than a second threshold. In some embodiments, thedetermination may be performed by the duration comparison block 904. Theselection of the second threshold may be performed based on the rhythmof the motion represented by the motion signal. See relevant descriptionwith reference to 904 in FIG. 9. For illustration purposes, the durationof the motion signal may include the duration of the respiratory motionsignal (e.g., t₂−t₁ illustrated in formula (7)) used to determine theone or more values of the symmetry related parameter. The secondthreshold may include a value of time period determined by a user, e.g.,100 seconds. The duration comparison block 904 may compare the durationof the respiratory motion signal with the second threshold. If theduration of the respiratory motion signal is below the second threshold,the process 1000 may proceed to 1014; otherwise, the process 1000 mayproceed to 1008.

In 1008, a determination may be made as to whether the one or morevalues of the symmetry related parameter are various or sufficientlyconsistent. In some embodiments, the determination may be performed bythe variation determination block 906. For illustration purposes, if theone or more values of the symmetry related parameter as illustrated informula (7) are all positive or negative, the variation determinationblock 906 may determine that the one or more values of the symmetryrelated parameter are sufficiently consistent; otherwise, the variationdetermination block 906 may determine that the one or more values of thesymmetry related parameter are various or inconsistent. If the one ormore values of the symmetry related parameter are determined to beinconsistent, the process 1000 may proceed to 1014; otherwise, theprocess 1000 may proceed to 1010.

In 1010, a determination may be made as to whether SNR corresponding tothe motion signal exceeds a third threshold. In some embodiments, thedetermination may be performed by the noise determination block 908. Ifthe SNR of the motion signal exceeds a third threshold, the process 1000may proceed to 1012; otherwise, the process 1000 may proceed to 1014.

In 1012, the credibility of the one or more values of the symmetryrelated parameter may be determined as credible.

In 1014, the credibility of the one or more symmetry related parametersmay be determined as incredible.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skills in the art,multiple variations and modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure.

For example, any operations of 1004, 1006, 1008, or 1010 may be omittedin the process 1000. For example, operation 1010 may be omitted, and thecredibility determination sub-unit 502 may determine whether the one ormore values of the symmetry related parameter are credible based onoperations 1004, 1006, and 1008. As another example, all of 1004, 1006,1008, 1010 may be omitted, and in such a case the credibilitydetermination sub-unit 502 may consider the one or more values of thesymmetry related parameter credible. In some embodiments, the order ofthe operations of the process 1000 may be changed or adjusted. Forexample, operation 1006 may be performed before 1004, or any two or moreoperations of 1004, 1006, 1008, and 1010 may be performed at the sametime.

FIG. 11 illustrates an exemplary respiratory motion signal according tosome embodiments of the present disclosure. As shown in FIG. 11, theamplitude of the respiratory motion signal changes over time. Differentreference lines, such as, line α, line β, or line γ, are presented withrespect to different exemplary techniques to determine a reference lineas described in the disclosure. A candidate EIP and a candidate EEP aremarked at a crest and a trough of the respiratory motion signal,respectively.

FIG. 12 illustrates a first exemplary division of a respiratory motionsignal according to some embodiments of the present disclosure. As shownin FIG. 12, the respiratory motion signal is divided into n sections bythe dashed lines. The ECT data may be gated into n frames based on the nsections. For example, the first section corresponds gated ECT data 1, .. . , and the last section corresponds to the gated ECT data n. Theamplitude intervals of different sections may be different.

FIG. 13 illustrates a second exemplary division of a respiratory motionsignal according to some embodiments of the present disclosure. As shownin FIG. 13, the respiratory motion signal is divided into n sectionsevenly in terms of the interval of the motion amplitude by the dashedlines.

FIG. 14 illustrates a third exemplary division of a respiratory motionsignal according to some embodiments of the present disclosure. As shownin FIG. 14, a respiratory cycle of the respiratory motion signal isdivided into four sections by the dashed lines. The time intervals ofdifferent sections may be the same or different.

Having thus described the basic concepts, it may be rather apparent tothose skilled in the art after reading this detailed disclosure that theforegoing detailed disclosure is intended to be presented by way ofexample only and is not limiting. Various alterations, improvements, andmodifications may occur and are intended to those skilled in the art,though not expressly stated herein. These alterations, improvements, andmodifications are intended to be suggested by this disclosure, and arewithin the spirit and scope of the exemplary embodiments of thisdisclosure.

Moreover, certain terminology has been used to describe embodiments ofthe present disclosure. For example, the terms “one embodiment,” “anembodiment,” and/or “some embodiments” mean that a particular feature,structure or characteristic described in connection with the embodimentis included in at least one embodiment of the present disclosure.Therefore, it is emphasized and should be appreciated that two or morereferences to “an embodiment” or “one embodiment” or “an alternativeembodiment” in various portions of this specification are notnecessarily all referring to the same embodiment. Furthermore, theparticular features, structures or characteristics may be combined assuitable in one or more embodiments of the present disclosure.

Further, it will be appreciated by one skilled in the art, aspects ofthe present disclosure may be illustrated and described herein in any ofa number of patentable classes or context including any new and usefulprocess, machine, manufacture, or composition of matter, or any new anduseful improvement thereof. Accordingly, aspects of the presentdisclosure may be implemented entirely hardware, entirely software(including firmware, resident software, micro-code, etc.) or combiningsoftware and hardware implementation that may all generally be referredto herein as a “unit,” “module,” or “system.” Furthermore, aspects ofthe present disclosure may take the form of a computer program productembodied in one or more computer readable media having computer readableprogram code embodied thereon.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including electro-magnetic, optical, or thelike, or any suitable combination thereof. A computer readable signalmedium may be any computer readable medium that is not a computerreadable storage medium and that may communicate, propagate, ortransport a program for use by or in connection with an instructionexecution system, apparatus, or device. Program code embodied on acomputer readable signal medium may be transmitted using any appropriatemedium, including wireless, wireline, optical fiber cable, RF, or thelike, or any suitable combination of the foregoing.

Computer program code for carrying out operations for aspects of thepresent disclosure may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB. NET,Python or the like, conventional procedural programming languages, suchas the “C” programming language, Visual Basic, Fortran 2103, Perl, COBOL2102, PHP, ABAP, dynamic programming languages such as Python, Ruby andGroovy, or other programming languages. The program code may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider) or in a cloud computing environment or offered as aservice such as a Software as a Service (SaaS).

Furthermore, the recited order of processing elements or sequences, orthe use of numbers, letters, or other designations therefore, is notintended to limit the claimed processes and methods to any order exceptas may be specified in the claims. Although the above disclosurediscusses through various examples what is currently considered to be avariety of useful embodiments of the disclosure, it is to be understoodthat such detail is solely for that purpose, and that the appendedclaims are not limited to the disclosed embodiments, but, on thecontrary, are intended to cover modifications and equivalentarrangements that are within the spirit and scope of the disclosedembodiments. For example, although the implementation of variouscomponents described above may be embodied in a hardware device, it mayalso be implemented as a software only solution, for example, aninstallation on an existing server or mobile device.

Similarly, it should be appreciated that in the foregoing description ofembodiments of the present disclosure, various features are sometimesgrouped together in a single embodiment, figure, or description thereoffor the purpose of streamlining the disclosure aiding in theunderstanding of one or more of the various inventive embodiments. Thismethod of disclosure, however, is not to be interpreted as reflecting anintention that the claimed subject matter requires more features thanare expressly recited in each claim. Rather, inventive embodiments liein less than all features of a single foregoing disclosed embodiment.

In some embodiments, the numbers expressing quantities or propertiesused to describe and claim certain embodiments of the application are tobe understood as being modified in some instances by the term “about,”“approximate,” or “substantially.” For example, “about,” “approximate,”or “substantially” may indicate ±20% variation of the value itdescribes, unless otherwise stated. Accordingly, in some embodiments,the numerical parameters set forth in the written description andattached claims are approximations that may vary depending upon thedesired properties sought to be obtained by a particular embodiment. Insome embodiments, the numerical parameters should be construed in lightof the number of reported significant digits and by applying ordinaryrounding techniques. Notwithstanding that the numerical ranges andparameters setting forth the broad scope of some embodiments of theapplication are approximations, the numerical values set forth in thespecific examples are reported as precisely as practicable.

Each of the patents, patent applications, publications of patentapplications, and other material, such as articles, books,specifications, publications, documents, things, and/or the like,referenced herein is hereby incorporated herein by this reference in itsentirety for all purposes, excepting any prosecution file historyassociated with same, any of same that is inconsistent with or inconflict with the present document, or any of same that may have alimiting affect as to the broadest scope of the claims now or laterassociated with the present document. By way of example, should there beany inconsistency or conflict between the description, definition,and/or the use of a term associated with any of the incorporatedmaterial and that associated with the present document, the description,definition, and/or the use of the term in the present document shallprevail.

In closing, it is to be understood that the embodiments of theapplication disclosed herein are illustrative of the principles of theembodiments of the application. Other modifications that may be employedmay be within the scope of the application. Thus, by way of example, butnot of limitation, alternative configurations of the embodiments of theapplication may be utilized in accordance with the teachings herein.Accordingly, embodiments of the present application are not limited tothat precisely as shown and described.

1. A method implemented on at least one machine each of which has atleast one processor and storage, the method comprising: acquiring amotion signal; determining one or more values of a symmetry relatedparameter of the motion signal; determining that the motion signal isflipped based on the one or more values of the symmetry relatedparameter; and correcting, in response to the determination that themotion signal is flipped, the motion signal.
 2. The method of claim 1,the acquiring a motion signal comprising: acquiring a respiratory motionsignal based on Emission Computed Tomography (ECT) data.
 3. The methodof claim 1, the determining one or more values of a symmetry relatedparameter of the motion signal comprising: determining a reference linewith respect to the motion signal.
 4. The method of claim 3, the motionsignal comprising a respiratory motion signal, the determining one ormore values of a symmetry related parameter of the motion signalcomprising: identifying an end of a candidate inspiration phase(candidate EIP) and an end of a candidate expiration phase (candidateEEP) in the respiratory motion signal based on the reference line,wherein an amplitude of the candidate EIP is a peak amplitude of therespiratory motion signal, and an amplitude of the candidate EEP is avalley amplitude of the respiratory motion signal, wherein the referenceline is midway between the candidate EIP and the candidate EEP such thatthe amplitude of the candidate EIP is equal to the amplitude of thecandidate EEP; and determining the one or more values of the symmetryrelated parameter of the motion signal based on a duration related tothe candidate EIP and a duration related to the candidate EEP.
 5. Themethod of claim 3, the motion signal comprising a respiratory motionsignal, the determining one or more values of a symmetry relatedparameter of the motion signal comprising: determining a durationrelated to a candidate inspiration phase and a duration of a candidateexpiration phase based on the reference line, wherein the reference lineis such that the duration of the candidate inspiration phase is equal tothe duration of the candidate expiration phase; identifying one or moreends related to the candidate inspiration phases (candidate EIPs) andone or more ends of the candidate expiration phase (candidate EEPs);determining a peak amplitude of the one or more candidate EIPs of themotion signal with respect to the reference line, and a valley amplitudeof the one or more candidate EEPs of the motion signal with respect tothe reference line; and determining the one or more values of thesymmetry related parameter of the motion signal based on the peakamplitude and the valley amplitude.
 6. The method of claim 3, the motionsignal comprising a respiratory motion signal, the determining areference line of the motion signal comprising: determining a referenceline of the respiratory motion signal based on a first criterionincluding a combination of an amplitude and a duration of therespiratory motion signal.
 7. The method of claim 6, the determining oneor more values of a symmetry related parameter of the motion signalcomprising: determining one or more values of the symmetry relatedparameter of the respiratory motion signal based on a second criterionincluding a combination of a weighted amplitude and the duration of therespiratory motion signal with respect to the reference line.
 8. Themethod of claim 3, the determining that the motion signal is flippedcomprising: determining credibility of the one or more values of thesymmetry related parameter.
 9. The method of claim 8, the determiningcredibility of the one or more values of the symmetry related parametercomprising: determining whether the one or more values of the symmetryrelated parameter are below a first threshold; or determining whether aduration of the respiratory motion signal is less than a secondthreshold; or determining a variation among the one or more values ofthe symmetry related parameter; or determining whether a signal to noiseratio corresponding to the respiratory motion signal exceeds a thirdthreshold.
 10. The method of claim 8, the determining that the motionsignal is flipped comprising: determining, in response to adetermination that the one or more values of the symmetry relatedparameter are incredible, that the respiratory motion signal is flippedbased on a plurality of images reconstructed based on the ECT data. 11.The method of claim 10, the determining that the respiratory motionsignal is flipped based on a plurality of images reconstructed based onthe ECT data further comprising: gating, based on the respiratory motionsignal, the ECT data into a plurality of frames; reconstructing theplurality of images, an image of the plurality of images correspondingto a frame of the plurality of frames of the ECT data; registering atleast two of the plurality of images; determining a motion of a point ofinterest based on the registration; and determining that the respiratorymotion signal is flipped based on the motion of the point of interest.12. The method of claim 11, wherein each frame of the plurality offrames of the ECT data corresponds to a same number of ECT events. 13.The method of claim 11, wherein each frame of the plurality of frames ofthe ECT data corresponds to a same amplitude interval, or a same timeinterval.
 14. The method of claim 11, the registering at least two ofthe plurality of images comprising: registering the at least two of theplurality of images based on an approach of sum square error (SSE). 15.A system, comprising: at least one computer-readable storage mediumincluding a set of instructions; at least one processor in communicationwith the at least one computer-readable storage medium, wherein whenexecuting the set of instructions, the at least one processor isdirected to: acquire a respiratory motion signal based on ECT data;determine one or more values of a symmetry related parameter of therespiratory motion signal; determine, based on the one or more values ofthe symmetry related parameter, that the respiratory motion signal isflipped; and correct, in response to the determination that therespiratory motion signal is flipped, the respiratory motion signal. 16.The system of claim 15, wherein the at least one processor is furtherdirected to: determine a reference line with respect to the respiratorymotion signal, wherein the one or more values of the symmetry relatedparameter of the respiratory motion signal are determined based on thereference line.
 17. The system of claim 15, wherein the at least oneprocessor is further directed to: determine that the one or more valuesof the symmetry related parameter are incredible; in response to thedetermination that the one or more values of the symmetry relatedparameter are incredible, gate, based on the respiratory motion signal,the ECT data into a plurality of frames; reconstruct a plurality ofimages, an image of the plurality of images corresponding to a frame ofthe plurality of frames of the ECT data; register at least two of theplurality of images; determine a motion of a point of interest based onthe registration; and determine, based on the motion of the point ofinterest, that the respiratory motion signal is flipped.
 18. A methodimplemented on at least one machine each of which has at least oneprocessor and storage, the method comprising: acquiring EmissionComputed Tomography (ECT) data of a subject; determining a motion signalbased on the ECT data; determining one or more values of a symmetryrelated parameter of the motion signal; determining that the motionsignal is flipped based on the one or more values of the symmetryrelated parameter; and correcting, in response to the determination thatthe motion signal is flipped, the motion signal.
 19. The method of claim18, further comprising: reconstructing a plurality of images, each ofthe plurality of images corresponding to a frame of the ECT data;determining a motion of a point of interest based on a registrationbetween at least two of the plurality of images; and determining thatthe motion signal is flipped based on the one or more values of thesymmetry related parameter and the motion of the point of interest. 20.The method of claim 18, the determining the one or more values of thesymmetry related parameter of the motion signal comprising: determininga reference line with respect to the motion signal. 21.-25. (canceled)